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Field
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differential equation models of bacterial persistence. A particular challenge, both for simulation and for machine learning, lies in the high dimensionality of these equations, which causes grid-based numerical
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machine learning approaches Collaborating with experimental and clinical research partners Support and preparation of scientific reports and journal articles
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on correlation-based machine learning. When an agricultural system fails due to compounding climate extremes - like a simultaneous heatwave, drought, and ozone pollution spike - standard models can forecast the
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. Desirable Criteria Experience implementing machine learning or deep learning models (e.g., neural networks, probabilistic learning methods). Knowledge of state estimation techniques, such as Kalman filters
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, SIAM Review, 60(3):550–591 (2018). [4] Diederik P Kingma and Max Welling, Auto-Encoding Variational Bayes, International Conference on Learning Representations (ICLR) 2014 ArXiv. http://arxiv.org/abs
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for part-time employment. Starting date: 27.03.2026 Job description:PhD position on physics-based machine learning modeling for materials and process design Reference code: 2026/WD 1 Commencement date
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Computational Mechanics. Solid background in continuum mechanics and numerical modeling Strong interest in machine learning and scientific computing Experience with numerical methods for PDEs and data-driven
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are looking for candidates with: An interest in developing mathematical methods and machine learning models good communication skills with sufficient proficiency in oral and written English, an excellent
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regimes; and machine learning, capturing complex nonlinear behaviour at the cost of model opacity. BENEFIT synthesises these paradigms by integrating stability analysis directly into machine learning
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and ML pipelines for drug synergy, write code for data analysis and post-processing data. Training of models like CNN, RNN, Transformers with some work in classical machine learning with XGBDTs is